Machine Learning Operations Engineer

Job Description

Job Description

Our Mission

Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives.

Machine Learning Operations (ML-Ops) Engineers build infrastructure that supports the entire lifecycle of Machine Learning (ML) projects from development to scaling and to deployment. If you have a passion for building the foundation that enables robotics research and engineering, you will want to join us!

What You Will Do

• Design, develop, and maintain company-wide platforms and tooling that utilize Kubernetes infrastructure to enable machine learning and data processing applications
• Enable self-service access to ML-compute for our on-prem and cloud compute clusters, including support for job scheduling, workload scalability and workload fault tolerance
• Enhance observability across ML applications through integrations with tools and services such as FluentD, Prometheus, Grafana and DataDog
• Integrate ML applications with experiment tracking and management services like Weights and Biases
• Elevate code quality and champion best practices in our engineering processes
• Collaborate with Machine Learning Engineers, Data Engineers, DEVOPs engineers and researchers to build scalable solutions that improve engineering and research velocity.

What You Will Bring

Extra Skills We Value

We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.